1 | #region License Information
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2 | /* HeuristicLab
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3 | * Copyright (C) 2002-2008 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
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4 | *
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5 | * This file is part of HeuristicLab.
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6 | *
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7 | * HeuristicLab is free software: you can redistribute it and/or modify
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8 | * it under the terms of the GNU General Public License as published by
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9 | * the Free Software Foundation, either version 3 of the License, or
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10 | * (at your option) any later version.
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11 | *
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12 | * HeuristicLab is distributed in the hope that it will be useful,
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13 | * but WITHOUT ANY WARRANTY; without even the implied warranty of
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14 | * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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15 | * GNU General Public License for more details.
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16 | *
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17 | * You should have received a copy of the GNU General Public License
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18 | * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>.
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19 | */
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20 | #endregion
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21 |
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22 | using System;
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23 | using System.Collections.Generic;
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24 | using System.Text;
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25 | using HeuristicLab.Core;
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26 | using HeuristicLab.Data;
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27 | using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
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28 |
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29 | namespace HeuristicLab.Random {
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30 | /// <summary>
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31 | /// Normally distributed random number generator.
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32 | /// </summary>
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33 | [EmptyStorableClass]
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34 | public class NormalRandomizer : OperatorBase {
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35 | private static int MAX_NUMBER_OF_TRIES = 100;
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36 |
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37 | /// <inheritdoc select="summary"/>
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38 | public override string Description {
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39 | get { return "Initializes the value of variable 'Value' to a random value normally distributed with 'Mu' and 'Sigma'."; }
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40 | }
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41 |
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42 | /// <summary>
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43 | /// Gets or sets the value for µ.
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44 | /// </summary>
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45 | /// <remarks>Gets or sets the variable with the name <c>Mu</c> through the method
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46 | /// <see cref="OperatorBase.GetVariable"/> of class <see cref="OperatorBase"/>.</remarks>
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47 | public double Mu {
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48 | get { return ((DoubleData)GetVariable("Mu").Value).Data; }
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49 | set { ((DoubleData)GetVariable("Mu").Value).Data = value; }
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50 | }
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51 | /// <summary>
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52 | /// Gets or sets the value for sigma.
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53 | /// </summary>
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54 | /// <remarks>Gets or sets the variable with the name <c>Sigma</c> through the method
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55 | /// <see cref="OperatorBase.GetVariable"/> of class <see cref="OperatorBase"/>.</remarks>
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56 | public double Sigma {
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57 | get { return ((DoubleData)GetVariable("Sigma").Value).Data; }
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58 | set { ((DoubleData)GetVariable("Sigma").Value).Data = value; }
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59 | }
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60 |
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61 | /// <summary>
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62 | /// Initializes a new instance of <see cref="NormalRandomizer"/> with four variable infos
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63 | /// (<c>Mu</c>, <c>Sigma</c>, <c>Value</c> and <c>Random</c>).
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64 | /// </summary>
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65 | public NormalRandomizer() {
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66 | AddVariableInfo(new VariableInfo("Mu", "Parameter mu of the normal distribution", typeof(DoubleData), VariableKind.None));
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67 | GetVariableInfo("Mu").Local = true;
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68 | AddVariable(new Variable("Mu", new DoubleData(0.0)));
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69 |
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70 | AddVariableInfo(new VariableInfo("Sigma", "Parameter sigma of the normal distribution", typeof(DoubleData), VariableKind.None));
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71 | GetVariableInfo("Sigma").Local = true;
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72 | AddVariable(new Variable("Sigma", new DoubleData(1.0)));
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73 |
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74 | AddVariableInfo(new VariableInfo("Value", "The value to manipulate (actual type is one of: IntData, DoubleData, ConstrainedIntData, ConstrainedDoubleData)", typeof(IObjectData), VariableKind.In));
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75 | AddVariableInfo(new VariableInfo("Random", "The random generator to use", typeof(MersenneTwister), VariableKind.In));
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76 | }
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77 |
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78 | /// <summary>
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79 | /// Generates a new normally distributed random variable and assigns it to the specified variable
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80 | /// in the given <paramref name="scope"/>.
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81 | /// </summary>
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82 | /// <param name="scope">The scope where to assign the new random value to.</param>
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83 | /// <returns><c>null</c>.</returns>
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84 | public override IOperation Apply(IScope scope) {
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85 | IObjectData value = GetVariableValue<IObjectData>("Value", scope, false);
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86 | MersenneTwister mt = GetVariableValue<MersenneTwister>("Random", scope, true);
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87 | double mu = GetVariableValue<DoubleData>("Mu", scope, true).Data;
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88 | double sigma = GetVariableValue<DoubleData>("Sigma", scope, true).Data;
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89 |
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90 | NormalDistributedRandom n = new NormalDistributedRandom(mt, mu, sigma);
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91 | RandomizeNormal(value, n);
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92 | return null;
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93 | }
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94 |
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95 | private void RandomizeNormal(IObjectData value, NormalDistributedRandom n) {
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96 | // dispatch manually based on dynamic type
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97 | if (value is IntData)
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98 | RandomizeNormal((IntData)value, n);
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99 | else if (value is DoubleData)
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100 | RandomizeNormal((DoubleData)value, n);
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101 | else throw new InvalidOperationException("Can't handle type " + value.GetType().Name);
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102 | }
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103 |
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104 | /// <summary>
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105 | /// Generates a new double random number based on a continuous, normally distributed random number
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106 | /// generator <paramref name="normal"/>.
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107 | /// </summary>
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108 | /// <param name="data">The double object where to assign the new value to.</param>
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109 | /// <param name="normal">The continuous, normally distributed random variable.</param>
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110 | public void RandomizeNormal(DoubleData data, NormalDistributedRandom normal) {
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111 | data.Data = normal.NextDouble();
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112 | }
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113 |
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114 | /// <summary>
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115 | /// Generates a new int random number based on a continuous, normally distributed random number
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116 | /// generator <paramref name="normal"/>.
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117 | /// </summary>
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118 | /// <param name="data">The int object where to assign the new value to.</param>
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119 | /// <param name="normal">The continuous, normally distributed random variable.</param>
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120 | public void RandomizeNormal(IntData data, NormalDistributedRandom normal) {
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121 | data.Data = (int)Math.Round(normal.NextDouble());
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122 | }
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123 | }
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124 | }
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